Abstract
Objectives
The objectives of this study were to: (1) examine whether the smoking status of the Canadian population is associated with a reduction in health-related quality of life (HRQoL); (2) calculate the overall economic burden of loss in HRQoL using a commonly accepted $100,000 willingness-to-pay (WTP) threshold to gain one quality-adjusted life year (QALY); and (3) calculate the loss of HRQoL over a lifetime.
Methods
We used the 2015 Canadian Community Health Survey. The variations in HRQoL were estimated using a multivariable generalized linear model. Total expected lifetime QALYs lost due to smoking were calculated by compounding the annual adjusted health utility loss associated with smoking across a respondent’s remaining years of life expectancy stratified by age. A discount rate of 1.5% was applied to the analysis based on recent analysis of the costs of borrowing in Canada.
Results
Smoking is significantly associated with HRQoL loss. This study demonstrated that smoking is associated with a 0.05 and 0.01 reduction in Health Utilities Index Mark 3 (HUI3) score for current and former smokers, which also corresponds to a loss of 0.66 quality-adjusted life years in average, and also is associated with substantial individual and societal economic cost. The total lifetime economic burden of HUI3 loss per smoker was $65,935, yielding in the aggregate a societal burden of $1068.88 billion in the study population.
Conclusion
Tobacco control, prevention and intervention not only will improve HRQoL but also will generate social returns on investment.
Keywords: Health-related quality of life, Smoking, Economic burden
Résumé
Objectifs
Dans cette étude, nous avons voulu : 1) déterminer si l’usage du tabac dans la population canadienne est associé à une diminution de la qualité de vie liée à la santé (QVLS); 2) calculer le fardeau économique global de la perte de QVLS à l'aide d’un seuil communément accepté, soit la volonté de payer 100 000 $ pour gagner une année de survie ajustée pour la qualité de vie (SAQV); et 3) calculer la perte de QVLS sur toute une vie.
Méthodes
Nous avons utilisé l’édition 2015 de l’Enquête sur la santé dans les collectivités canadiennes. Les écarts dans la QVLS ont été estimés à l'aide d’un modèle linéaire généralisé multivarié. Le nombre prévu d’années de SAQV perdues en raison du tabagisme sur toute une vie a été calculé en additionnant la perte annuelle de services publics de santé associée au tabagisme sur la durée de vie restante de l’espérance de vie d’un répondant, stratifiée selon l’âge. Un taux de réduction de 1,5 % a été appliqué à l’analyse d’après une analyse récente des coûts d’emprunt au Canada.
Résultats
Le tabagisme présente une corrélation significative avec la perte de QVLS. L’étude montre qu’il est associé à une diminution de 0,05 et de 0,01 du HUI3 (Health Utilities Index Mark 3) pour les fumeurs actuels et les anciens fumeurs, respectivement, ce qui correspond aussi à une diminution de 0,66 de la survie ajustée pour la qualité de vie en moyenne, en plus d’être associé à un coût considérable pour l’individu et pour la société. Le fardeau économique total de la baisse du HUI3 sur la vie d’un fumeur était de 65 935 $, soit un fardeau sociétal global de 1 068,88 milliards de dollars dans la population étudiée.
Conclusion
Les mesures de prévention, de contrôle et d’intervention liées au tabagisme améliorent la QVLS, mais ce sont aussi des investissements qui génèrent des rendements sociaux.
Mots-clés: Qualité de vie liée à la santé, Fumer, Fardeau économique
Introduction
Cigarette smoking is one of the major public health issues worldwide. Despite a significant decrease in the prevalence of smoking in Canada, tobacco use is still one of the most harmful behaviours related to a number of preventable diseases and premature death. Furthermore, it poses enormous health and societal costs. Tobacco use causes substantial healthcare expenditures and lost productivity due to morbidity and mortality each year. Individuals who reported having ever smoked have significantly higher healthcare utilization rates—including physician visits, hospitalizations, hospital length of stay, pharmaceutical use—than those who reported having never smoked, after controlling for demographic, morbidity and behavioural risk factors (Martens et al. 2015; Azagba et al. 2013). Smoking status is associated with elevated rates of potential years of life lost, mortality, reduced life expectancy and cancer burden. In Canada, 21% of all deaths are attributable to tobacco use in the past decade (Statistics Canada 2016a). Tobacco kills three times more Canadians each year than alcohol, AIDS, illegal drugs, car accidents, suicide and murder combined (Centre for Addiction and Mental Health 2018). The adverse effects of smoking on the health of individuals have been well established (Cunningham et al. 2015; Berstad et al. 2015). Smoking is highly associated with not only premature mortality, but also a worse subjective well-being and physical health, such as pain/discomfort and increased anxiety.
Health-related quality of life (HRQoL) is a multidimensional concept that includes physical, mental, social and emotional functioning. It is closely related to the concept of ‘well-being’. It goes beyond direct measures of population health, such as mortality and life expectancy, and attempts to measure the impact of health on quality of life. Different tools have been used to measure HRQoL and these differ mainly in terms of which dimensions are captured and how finely each is measured. HRQoL is an important way of measuring one aspect of the economic burden of smoking that is generally ignored—the reduction in quality of life realized by a smoker before chronic conditions and premature mortality occur.
There are very few studies that explore the relationship between smoking and HRQoL in the general population; Vogl et al. (2012) is a rare exception, which measured the loss of HRQoL realized by English smokers (Vogl et al. 2012). To our knowledge, there is no study focused on smoking and quality of life controlling for socio-economic, chronic disease and lifestyle factors for the Canadian general population. Our study objectives were to: (1) examine whether the smoking status of the Canadian population is associated with a reduction in HRQoL once socio-economic, chronic disease and lifestyle conditions are controlled for; (2) calculate the overall economic burden of loss in HRQoL using a commonly accepted $100,000 willingness-to-pay (WTP) threshold to gain one quality-adjusted life year (QALY); and (3) calculate the loss of HRQoL over a lifetime.
Methods
Data source
We used the 2015 Canadian Community Health Survey (CCHS). The CCHS is a cross-sectional survey that gathers health-related data for the Canadian population. It represents 98% of the Canadian population aged 12 and over living in ten provinces and three territories. The CCHS excludes persons living on reserves and other Aboriginal settlements in the provinces, full-time members of the Canadian Forces, the institutionalized population, and children aged 12–17 who are living in foster care, resulting in an overall person-level response rate of 60% (Statistics Canada 2016b).
Study sample
Because studies have suggested that substantial uptake of smoking occurs after 15 years of age (Edwards et al. 2013), for the purpose of this study, individuals aged 15 and over are included. In the CCHS, type of smoker is a derived variable based on responses to questions on smoking habits. This variable includes lifetime cigarette consumption. We used this derived variable to identify the type of smokers for main measure. The following categories are used: ‘Current smoker’ (includes daily smoker, occasional daily smoker who previously was a daily smoker, and always an occasional smoker), ‘Former smoker’ (includes former daily smoker and former occasional smoker) and ‘Non-Smoker’ (never smoked).
Study measures
The Health Utilities Index (HUI) was developed by a multidisciplinary team at McMaster University, Canada (Feeny et al. 2001). HUI is a rating scale used to measure general health status and HRQoL. HUI questionnaires are designed to map onto two classification systems, Health Utility Index Mark 2 and Health Utility Index Mark 3, measuring 24,000 and 972,000 unique health states respectively. HRQoL was assessed in this study using the HUI3, a generic preference-based measure that reflects the subjective values assigned to specific health-related outcomes. The HUI3 is a validated instrument and has been used in hundreds of studies and clinical settings (Raat et al. 2002; Bosch and Hunink 2000). HUI3 quantifies HRQoL based on an individual’s functional status in eight domains (attributes)—vision, hearing, speech, mobility, dexterity, emotion, cognition and pain—each of which has five or six levels, allowing description of 972,000 health states. Overall, HUI3 scores are calculated from a multiplicative, multi-attribute utility model based on preference scores obtained from a random sample of the Canadian population, using an interval scale in which dead = 0.00 and perfect health = 1.00; scores below zero could represent health states considered to be worse than dead. HUI3 scores meet or exceed the criteria for calculating QALY, and the requirements of published guidelines for economic evaluations of pharmaceutical and other healthcare services (Horsman et al. 2003).
Socio-economic and demographic factors
The respondents are classified by four age groups: (1) 15–24 years old; (2) 25–44 years old; (3) 45–64 years old; (4) 65 and older. A close link between smoking behaviour and individual socio-economic status has been well documented (Laaksonen et al. 2005; Huang and Ren 2011). Thus, a number of socio-economic factors were included in this study. For example, respondents are grouped by (1) education level (less than secondary school; secondary school graduation, no post-secondary education; post-secondary certificate diploma or university degree); (2) marital status (married or living as a couple versus not living as a couple [single, divorced, separated or widowed]); (3) household income levels are determined based on a combination of the number of people in the household, and the total household income from all sources in the past 12 months (Region of Peel 2018), including four categories: lowest income, lower-middle income, middle-upper income, and highest income.
Health-related factors
Evidence has revealed that smokers are more likely to develop heart disease, diabetes and respiratory diseases (Centers for Disease Control and Prevention 2018). However, the purpose of this paper is to measure the reduction in HRQoL that is not manifested in measurable morbidity. Therefore, based on the availability of data from the source survey, we controlled for the following health-related factors: feeling stressed (not at all to not very stressed versus a bit to extremely stressed) and presence of a chronic disease (i.e., had at least one of asthma, chronic bronchitis, emphysema or COPD, heart disease, diabetes, versus no chronic condition).
Behavioural and lifestyle factors
Drinking alcohol and smoking tobacco commonly occur together (Burton and Tiffany 1997). However, excess drinking can also result in losses of HRQoL. Therefore, we included a drinking behaviour variable: in 2015 CCHS according to drinking habits, the type of alcohol drinker was created by grouping individuals into three groups: regular drinkers, occasional drinkers, and no drink in the past 12 months.
Body mass index (BMI) is a method of classifying body weight according to health risk. Thus, BMI was calculated according to age range. BMI for youths is different from that of adults as they are still maturing. This indicator classifies children aged 12 to 17 (except female respondents aged 15 to 17 who were pregnant or did not answer the pregnancy question) as ‘obese’ or ‘overweight’ or ‘neither obese nor overweight’ according to the age- and sex-specific BMI cut-off points as defined by Cole et al. (2000). The Cole cut-off points have been applied to the CCHS since 2005 and are based on pooled international data (Brazil, Great Britain, Hong Kong, Netherlands, Singapore, and the USA) for BMI and linked to the internationally accepted adult BMI cut-off points of 25 (overweight) and 30 (obese). Respondents aged 12 to 17 whose BMIs do not fall in these categories have been classified as ‘neither obese nor overweight’. For adult respondents aged 18 and over (excluding pregnant women), BMI was calculated and also categorized into obese (BMI ≥ 30.0 kg/m2), overweight (BMI 25.0–29.9 kg/m2), and neither obese nor overweight (BMI < 25.0 kg/m2).
Economic burden analysis
Total individual expected lifetime QALYs loss due to smoking were calculated across the study population by compounding the annual adjusted health utility loss associated with smoking across a respondent’s remaining years of life expectancy stratified by age. The unit for health utility from the HUI3 is the QALY. A QALY is equivalent to 1 year spent in perfect health. A year spent in less than perfect health is represented by a value between zero and one, and is estimated by the HUI3. Data for ‘years to life expectancy’ were derived from the life table indicating the average number of years of life remaining across a population at a specific age (Statistics Canada 2018).
The discount rate allows us to measure the current value of something that will be received in the future. Typically, this is associated with future payments or streams of payments; a dollar today is worth more than a dollar you expect to receive at some point in the future. As is typical in economic analysis, we discounted future QALYs. A discount rate of 1.5% was utilized in all QALY estimates, reflecting recent empirical evidence on the long-term cost of borrowing for Canadian provinces (Canadian Agency for Drugs and Technologies in Health 2018). In this case, a 1.5% discount rate implies that the magnitude of the annual QALY losses due to smoking will decrease with every subsequent year by a factor of (1 + 0.015)−1 of the prior year’s value. We used a societal perspective to calculate the overall life time economic burden of HRQoL loss due to smoking using a commonly accepted $100,000 WTP threshold to gain one QALY (Neumann et al. 2014). A WTP threshold represents an estimate of what a representative consumer would be willing to pay for the health benefit in a particular society, based on what that society has been willing to pay for other health interventions. Sensitivity analyses were conducted to test the robustness of the results by examining the effect of varying discount rates and adjusting for reduced life expectancy by smoking behaviour. According to Statistics Canada (2015), smokers could lose about 9 years of life expectancy.
Statistical techniques
The demographic, socio-economic, chronic disease and behavioural factors (Table 1) were presented by mean and standard error (S.E.) for continuous variables and by percentage (95% CI) of total for categorical variables. The variations in health utilities were measured using a multivariable generalized linear model, allowing for response variables that have both Gaussian and non-Gaussian distributions (e.g., the sample distribution is the beta distribution in this study). Covariates included age, gender, marital status, smoking status, alcohol use, household income, BMI, life stress and suffering at least one chronic disease. All regression results and descriptive analyses are population weighted using the survey weights provided by Statistics Canada to produce population estimates and adjust for unequal probabilities of selection. All analyses were carried out using SAS version 9.4.
Table 1.
Weighted percentage (95% CI) of sample characteristics by smoking status
| Characteristics | Factor | Current smoker | Former smoker | Non-smoker | p |
|---|---|---|---|---|---|
| Demographic | |||||
| Age | Mean, SE | 43.25 (0.25) | 51.96 (0.16) | 41.67 (0.15) | < 0.0001 |
| Age group | 15–24 | 13.53 (12.20–14.86) | 5.99 (5.40–6.58) | 24.07 (23.11–25.02) | < 0.0001 |
| 25–44 | 38.76 (37.11–40.41) | 28.03 (27.06–29.01) | 34.93 (33.84–36.02) | ||
| 45–64 | 38.21 (36.68–39.75) | 40.74 (39.80–41.69) | 26.13 (25.27–26.99) | ||
| 65+ | 9.50 (8.66–10.33) | 25.34 (24.61–25.86) | 14.87 (14.34–15.40) | ||
| Sex | Male | 56.79 (55.22–58.36) | 53.97 (53.12–54.83) | 41.90 (41.01–42.78) | < 0.0001 |
| Female | 43.21 (41.64–44.78) | 46.03 (45.17–46.88) | 58.10 (57.22–58.99) | ||
| Socio-economic | |||||
| Total household income | Lowest income | 8.99 (7.99–9.98) | 3.60 (3.20–4.00) | 5.84 (5.23–6.44) | < 0.0001 |
| Lower-middle income | 17.23 (15.85–18.60) | 12.23 (11.56–12.90) | 14.18 (13.34–15.02) | ||
| Middle-upper income | 29.89 (28.33–31.45) | 27.37 (26.38–28.37) | 27.69 (26.56–28.82) | ||
| Highest income | 43.90 (42.24–45.56) | 56.97 (55.69–57.90) | 52.30 (51.02–53.58) | ||
| Education level | Less than secondary school graduation | 17.88 (16.64–19.11) | 13.03 (12.33–13.72) | 15.54 (14.85–16.23) | < 0.0001 |
| Secondary school graduation, no post-secondary education | 27.07 (25.52–28.61) | 21.00 (20.08–21.91) | 18.81 (17.87–19.74) | ||
| Post-secondary certificate diploma or university degree | 55.06 (53.32–56.80) | 65.98 (64.91–67.04) | 65.65 (64.60–66.70) | ||
| Marital status | Married or living as a couple | 50.87 (49.10–52.65) | 69.07 (67.96–70.18) | 55.37 (54.22–56.51) | < 0.0001 |
| Not living as a couple | 49.13 (47.35–50.90) | 30.93 (29.82–32.04) | 44.63 (43.49–45.78) | ||
| Health-related | |||||
| Health Utility Index | Mean, SE | 0.82 (0.003) | 0.86 (0.002) | 0.88 (0.002) | < 0.0001 |
| Vision impairment | Yes | 52.27 (50.53–54.01) | 61.42 (60.34–62.49) | 48.39 (47.18–49.61) | < 0.0001 |
| No | 47.73 (45.99–49.47) | 38.58 (37.51–39.66) | 51.61 (50.39–52.82) | ||
| Hearing impairment | Yes | 2.62 (2.14–3.11) | 4.63 (4.24–5.01) | 2.58 (2.26–2.91) | < 0.0001 |
| No | 97.38 (96.89–97.86) | 95.37 (94.99–95.76) | 97.42 (97.09–97.74) | ||
| Speech impairment | Yes | 1.49 (1.00–1.99) | 0.71 (0.52–0.91) | 0.98 (0.75–1.20) | < 0.0001 |
| No | 98.51 (98.01–99.00) | 99.29 (99.09–99.48) | 99.02 (98.80–99.25) | ||
| Mobility impairment | Yes | 5.09 (4.44–5.74) | 5.22 (4.82–5.62) | 3.91 (3.51–4.32) | < 0.0001 |
| No | 94.91 (94.26–95.56) | 94.78 (94.38–95.18) | 96.09 (95.68–96.49) | ||
| Dexterity impairment | Yes | 1.04 (0.68–1.39) | 0.61 (0.44–0.79) | 0.61 (0.42–0.80) | < 0.0001 |
| No | 98.96 (98.61–99.32) | 99.39 (99.21–99.56) | 99.39 (99.20–99.58) | ||
| Emotion impairment | Yes | 28.50 (26.97–30.03) | 21.08 (20.12–22.05) | 18.75 (17.82–19.69) | < 0.0001 |
| No | 71.50 (69.97–73.03) | 78.92 (77.96–79.88) | 81.25 (80.31–82.18) | ||
| Cognition impairment | Yes | 36.38 (34.75–38.02) | 30.67 (29.62–31.72) | 29.64 (28.61–30.67) | < 0.0001 |
| No | 63.62 (61.98–65.25) | 69.33 (68.28–70.38) | 70.36 (69.33–71.39) | ||
| Pain impairment | Yes | 26.39 (25.01–27.77) | 23.35 (22.38–24.31) | 16.86 (15.96–17.76) | < 0.0001 |
| No | 73.61 (72.23–74.99) | 76.65 (75.69–77.62) | 83.14 (82.24–84.04) | ||
| Has chronic disease* | At least one | 20.19 (18.85–21.52) | 21.11 (20.17–22.04) | 15.50 (14.59–16.40) | < 0.0001 |
| No | 79.81 (78.48–81.15) | 78.89 (77.96–79.83) | 84.50 (83.60–85.41) | ||
| Stress | Not at all to not very stressful | 31.05 (29.32–32.77) | 37.27 (36.20–38.34) | 61.40 (60.18–62.62) | < 0.0001 |
| A bit to extremely stressful | 68.95 (67.23–70.68) | 62.73 (61.66–63.80) | 38.60 (37.38–39.82) | ||
| Lifestyle and behavioural | |||||
| BMI | Neither obese nor overweight | 48.58 (46.84–50.31) | 40.61 (39.46–41.75) | 53.56 (52.30–54.82) | < 0.0001 |
| Overweight | 31.74 (30.12–33.36) | 37.60 (36.44–38.76) | 29.85 (28.73–30.97) | ||
| Obese | 19.69 (18.31–21.06) | 21.80 (20.87–22.72) | 16.59 (15.72–17.45) | ||
| Type of alcohol drinker | Regular drinker | 17.88 (16.64–19.11) | 13.03 (12.33–13.72) | 15.54 (14.85–16.23) | < 0.0001 |
| Occasional drinker | 27.07 (25.52–28.61) | 21.00 (20.08–21.91) | 18.81 (17.87–19.74) | ||
| No drink last 12 months | 55.06 (53.32–56.80) | 65.98 (64.91–67.04) | 65.65 (64.60–66.70) | ||
| Weighted observations | 5,176,925 | 11,034,309 | 12,131,376 | ||
Data source: Statistics Canada, 2015
*One of asthma, chronic bronchitis, emphysema or COPD, heart disease, diabetes
Results
Demographic, socio-economic, behavioural, chronic disease condition characteristics are presented according to smoking status. The mean age of the study population is 46 (S.E. 0.05), 18.3% were current smokers, 38.9% were former smokers and 42.8% were non-smokers. Of all survey participants, 49% were males. The smokers were more likely to live in lower socio-economic status (e.g., lower income and lower educational level), be obese and overweight, not live as a couple, have at least one chronic disease, feel stressed, and be alcohol drinkers. The scale of HUI3 is from − 0.329 to 1; the overall mean HUI3 was 0.86 (S.D. 0.002). Mean HUI3 was 0.04 lower for current smokers compared with former smokers (0.82 versus 0.86), and the difference was even bigger between current smokers and non-smokers (0.82 versus 0.88). Both current and former smokers had a higher proportion of loss in specific domains of HRQoL compared with non-smokers.
Table 2 presents the results of the multivariable generalized linear model analysis of variables associated with the overall HUI3 score. After controlling for demographic, socio-economic, behavioural and chronic disease factors, significant declines in HUI3 were observed among current and former smokers (p < 0.0001). Covariates are significantly associated with decreased overall HUI3 score, including people who were old, male, alcohol drinkers, not living as a couple, overweight and obese, had at least one chronic disease, had lower household income, felt a bit to extremely stressful.
Table 2.
Multivariable adjusted generalized linear model
| Regression variables | Coefficient estimate (standard error) | p |
|---|---|---|
| Age 15–24 | 0.06 (0.005) | < 0.0001 |
| Age 25–44 | 0.05 (0.004) | < 0.0001 |
| Age 45–64 | 0.02 (0.005) | < 0.0001 |
| Age 65+ | Reference | – |
| Current smoker | − 0.05 (0.004) | < 0.0001 |
| Former smoker | − 0.01 (0.003) | < 0.0001 |
| Non-smoker | Reference | – |
| Male | 0.02 (0003) | < 0.0001 |
| Female | Reference | – |
| Regular alcohol drinker | − 0.03 (0.005) | < 0.0001 |
| Occasional alcohol drinker | − 0.02 (0.004) | < 0.0001 |
| No drink last 12 months | Reference | – |
| Living as a couple | 0.02 (0.004) | < 0.0001 |
| Not living as a couple | Reference | – |
| Neither overweight nor obese | Reference | – |
| Overweight | − 0.01 (0.003) | 0.0007 |
| Obese | − 0.04 (0.004) | < 0.0001 |
| Lowest income | Reference | – |
| Lower-middle income | 0.03 (0.009) | 0.0003 |
| Middle-upper income | 0.06 (0.008) | < 0.0001 |
| Highest income | 0.09 (0.009) | < 0.0001 |
| Not at all to not very stressful | 0.05 (0.003) | < 0.0001 |
| A bit to extremely stressful | Reference | – |
| Not having a chronic disease | 0.02 (0.004) | < 0.0001 |
| Having at least one chronic disease* | Reference | – |
Data source: Statistics Canada, 2015
*One of asthma, chronic bronchitis, emphysema or COPD, heart disease, diabetes
Life time QALY losses were derived using a discount factor from the observation that the adjusted health utility (in QALY) for current and former smokers decreased by 0.05 and 0.01 respectively. Namely, the calculation is based on the linear model tracing the gap from the unadjusted remaining years to life expectancy, using an annual discount rate of 1.5%.The results demonstrated a total of 10,688,839 QALYs lost across the expected remaining lifetime of the study population, and this total number of QALYs was divided by the number of study population, resulting in an average lifetime loss of 0.66 QALYs per individual smoker (Table 3). Assuming a $100,000/QALY WTP, the average individual’s lifetime economic burden of HUI3 loss due to smoking behaviour categorized into four age groups was $122,953, $90,896, $55,624 and $23,763 for 15–24, 25–44, 45–64 and 65+ years of age respectively. When aggregated across the entire study population, the lifetime societal economic burden was $167.36, $463.57, $360.10 and $77.85 billion across the above age groups. The total lifetime economic burden of HUI3 loss per smoker was $65,935 yielding in the aggregate a societal burden of $1068.88 billion in the study population.
Table 3.
Economic burden of loss in HRQoL by age group
| Age group | Weighted number of smokers | Weighted average QALYs lost | Weighted population QALYs lost* | Willingness-to-pay/QALY | Weighted lifetime individual economic burden┼ | Weighted lifetime societal economic burden (billion)╫ |
|---|---|---|---|---|---|---|
| 15–24 | 1,361,174 | 1.23 | 1,673,611 | $100,000 | $122,953 | $167.36 |
| 25–44 | 5,100,000 | 0.91 | 4,635,716 | $100,000 | $90,896 | $463.57 |
| 45–64 | 6,473,885 | 0.56 | 3,601,009 | $100,000 | $55,624 | $360.10 |
| 65+ | 3,276,175 | 0.24 | 778,503 | $100,000 | $23,763 | $77.85 |
| Overall | 16,211,233 | 0.66 | 10,688,839 | $100,000 | $65,935 | $1068.88 |
| Assuming life expectancy for smoker is 9 years shorter | ||||||
| 15–24 | 1,361,174 | 1.11 | 1,512,091 | $100,000 | $111,087 | $151.21 |
| 25–44 | 5,100,000 | 0.78 | 4,002,010 | $100,000 | $78,471 | $400.20 |
| 45–64 | 6,473,885 | 0.41 | 2,659,054 | $100,000 | $41,074 | $265.90 |
| 65+ | 3,276,175 | 0.10 | 338,594 | $100,000 | $10,335 | $33.85 |
| Overall | 16,211,233 | 0.53 | 8,511,748 | $100,000 | $52,505 | $851.17 |
Data source: Statistics Canada, 2015
*Discount rate 1.5%
┼Product of population QALYs lost and $/QALY divided by number of smokers
╫Product of population QALYs lost and $/QALY
Statistics Canada estimates that the life expectancy of smokers is 9 years less than that of non-smokers. However, much of the reduced life expectancy occurs through comorbidities such as chronic conditions or associated lifestyle factors such as low income, for which we controlled. Using CCHS data, it is difficult to attribute expected loss of life years to any single factor, including smoking. When the analysis was adjusted based on smokers reduced life expectancy, the total loss of QALYs was 8,511,748, resulting in an average lifetime loss of 0.53 QALYs per smoker. The average individual’s lifetime economic burden due to smoking behaviour for each age group was $111,087, $78,471, $41,074 and $10,335 (Table 3). That is, the reduced HRQoL associated with smoking over a lifetime falls, somewhat paradoxically, when we adjust for the shorter life expectancy of smokers. A complete estimate of the economic burden of smoking would, however, include the economic costs associated with these 9 lost years, as well as the smoking-attributable losses of HRQoL associated with chronic conditions.
In order to determine the robustness of the study findings, Table 4 shows sensitivity analyses using different discount rates (0–3%). Outcomes were very sensitive to changes in the discount rate; the results based on unadjusted remaining years to life expectancy showed that the lifetime economic burden of the utility loss per smoker ranged from $50,787 to $89,618. Altering these parameters yielded an overall societal lifetime economic burden due to smoking ranging from $823.31 to $1452.81 billion. When the reduced years of life expectancy of smokers was considered, the average lifetime economic burden was in the range of $41,941 to $68,077.
Table 4.
Sensitivity analysis of economic burden of loss in HRQoL by age group
| Age group | Weighted number of smokers | Weighted average QALYs lost* | Weighted population QALYs lost* | Willingness-to-pay/QALY | Weighted lifetime individual economic burden┼ | Weighted lifetime societal economic burden (billion)╫ |
|---|---|---|---|---|---|---|
| 15–24 | 1,361,174 | 0.86–1.89 | 1,170,098–2,570,640 | $100,000 | $85,962–$188,854 | $117.00–$257.06 |
| 25–44 | 5,100,000 | 0.67–1.29 | 3,431,159–6,571,753 | $100,000 | $67,278–$128,858 | $343.11–$657.17 |
| 45–64 | 6,473,885 | 0.45–0.70 | 2,939,182–4,504,517 | $100,000 | $45,401–$69,580 | $293.91–$450.45 |
| 65+ | 3,276,175 | 0.21–0.27 | 692,699–881,269 | $100,000 | $21,144–$26,899 | $69.26–$88.12 |
| Overall | 16,211,233 | 0.51–0.90 | 8,233,138–14,528,179 | $100,000 | $50,787–$89,618 | $823.31–$1452.81 |
| Assuming life expectancy for smoker is 9 years shorter | ||||||
| 15–24 | 1,361,174 | 0.81–1.61 | 1,100,023–2,192,633 | $100,000 | $80,814–$161,084 | $110.00–$219.26 |
| 25–44 | 5,100,000 | 0.61–1.05 | 3,096,996–5,349,304 | $100,000 | $60,725–$104,888 | $309.69–$534.93 |
| 45–64 | 6,473,885 | 0.35–0.48 | 2,285,165–3,131,541 | $100,000 | $35,298–$48,372 | $228.51–$313.15 |
| 65+ | 3,276,175 | 0.09–0.11 | 316,958–362,653 | $100,000 | $9,674–$11,069 | $31.69–$36.26 |
| Overall | 16,211,233 | 0.42–0.68 | 6,799,142–11,036,132 | $100,000 | $41,941–$68,077 | $679.91–$1103.61 |
Data source: Statistics Canada, 2015
*Discount rate 0–3%
┼Product of population QALYs lost and $/QALY divided by number of smokers
╫Product of population QALYs lost and $/QALY
Discussion
In this paper, we examined the relationship between smoking and the HRQoL in the general Canadian population; our analyses offered evidence of a strong association between smoking behaviour and poor HRQoL outcomes and the magnitude of this association is determined by smoking status. For example, the loss in HRQoL is greater among current smokers than among former smokers. Our findings are consistent with some previous studies from other developed countries (Vogl et al. 2012; Jia and Lubetkin 2010; Laaksonen et al. 2006; Wilson et al. 1999; Strine et al. 2005). In addition, this study shows that smoking has a significant and independent impact on HRQoL after adjusting for a wide array of important covariates including socio-economic variables which have been considered as having a greater impact on HRQoL than smoking status itself (Tillmann and Silcock 1997). The 0.05 decrease in mean adjusted HUI3 score for current smokers is the largest HRQoL reduction observed from the generalized linear model regression. Findings from this current study can provide important information for smoking intervention programs about which health attributes (e.g., socio-economic status, alcohol use, obesity, and comorbidities) might be targeted for specific populations, such as women in particular age groups who are current smokers.
Since smokers can expect to lose about 9 years of life expectancy, we estimated lifetime economic burden by using the remaining years of life expectancy for the general population and adjusted life expectancy which was 9 years shorter due to smoking. This, however, almost certainly overadjusts for reduced life expectancy due to smoking alone, because many of the years of life lost are associated with the smoking-attributable portion of chronic conditions. Using lifetime QALYs loss, we estimate lifetime economic burden for each smoking status. The overall low HRQoL loss among individual smokers generates significant individual and societal economic implications. Even without taking into account the economic consequences from reduced work productivity (absence from labour force) and health expenditure to treat smoking-attributable disease, the loss in HRQoL is associated with an average $65,935 loss in individual welfare over the lifetime for the study population. When we adjusted the remaining years to life expectancy, the lifetime individual economic burden is $52,505.
Our study is subject to several limitations. First, the CCHS is self-reported; thus, recall bias may have particular impact on certain variables. For example, the respondents were asked about events (e.g., drinking alcohol) occurring during the past months, and their recall could be incorrect. Second, the CCHS survey covers 98% of the total population, but information from the other 2% population was excluded. This missed population may include those residing in shelters or the homeless who are at a high risk of drug abuse problems and a high risk of smoking. In addition, the response rate of CCHS 2015 may result in an underestimate of lifetime economic burden. Third, this study used cross-sectional data; therefore, the causal inference between the HRQoL outcome and smoking was precluded. Further investigations may benefit from the inclusion of longitudinal data. Finally, we controlled for many health conditions that are exacerbated by smoking. In that sense, we are systematically underestimating the costs of smoking. However, our purpose was to estimate those costs of smoking that are usually omitted in estimates of the economic burden of smoking. The attributable costs of chronic conditions are typically included in these estimates. Despite these limitations, this study provides some estimates of the loss of HRQoL by smoking status using a large sample size. This is the first study in Canada to examine the association of HRQoL and smoking status using a well-validated tool of HUI3. In addition, we used economic modelling to estimate lifetime loss in QALY and the relevant economic burden. This study is novel because most studies in the literature estimate economic burden from the healthcare system perspective only, while our study focused on the economic burden borne by individual smokers.
Conclusions
The results confirm that smoking is significantly associated with HRQoL loss in Canadian general population. This study also demonstrated that smoking is associated with a 0.05 and 0.01 reduction in HUI3 score for current and former smokers, which also corresponds to a loss of 0.66 quality-adjusted life years on average over a lifetime. This is associated with substantial individual and societal economic cost. This information provides important additional justification for the tobacco control policies; tobacco control, prevention and intervention will not only improve HRQoL but also will generate social returns on investment.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
Footnotes
Publisher’s note
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